Electronic storage mechanisms have enabled accumulation of massive amounts of data. For instance, data that previously required volumes of books for recordation can now be stored electronically without expense of printing paper and with a fraction of physical space needed for storage of paper. Many users employ database systems for storage and organization of data and query such databases to retrieve desirable data. Database systems have been widely deployed and applications associated therewith have become increasingly complex and varied.
Complex queries are common in decision support and reporting scenarios. Query optimization tends to be expensive for such complex queries despite development of techniques to cope with such queries. In addition, physical design tuning of databases has become more relevant. Thus, database administrators spend a considerable time either tuning a less than optimal installation for performance or maintaining a well-tuned installation over time.
Automated tools can tune the physical design of a database and recommend various physical structures, such as indexes and materialized views. However, these automated tools are resource intensive and it is common for tuning sessions to run for a long time before returning a useful recommendation.